Explore AI Agent Skills & Claude Prompts
Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.
Enter through keywords, occupations, creators, and GitHub sources to see what kinds of skills are emerging across domains.
Use the same catalog through the API
Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
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faq-mine
by BlackBeltTechnologyMine docs/faq.md from README.md and docs/*.md. Dispatches haiku subagents per source doc to extract recurring how-to / what-is questions, dedupes against existing FAQ, and merges entries in caveman style. Use when the user asks to "build / regenerate / extend the FAQ", "mine docs into FAQ", "create FAQ from README + docs", or "process knowledge into faq.md".
debug-dashboard
by BlackBeltTechnologyDiagnose problems in the running pi-agent-dashboard system. Tail ~/.pi/dashboard/server.log, probe /api/health for mode + uptime, check bridge WebSocket connectivity, triage vitest failures via tee→grep, inspect known-issue FAQ entries (Electron Node bin selection, Fastify + bad-Node crashes, stale-port hangs, single-instance lock). Routes UI/visual issues to the browser skill. Use when the server seems hung, a pi session won't connect, tests fail mysteriously, the dashboard shows a blank page, restart loops, port conflicts, or any "why isn't X working" / "the dashboard is doing Y" question.
jj-uncommit-to-working-copy
by BlackBeltTechnologyIn a jj-colocated git repo, take a jj commit (default `@-`, the parent of the working copy) and fold its changes into the working copy as undescribed changes — equivalent to "uncommitting" so they re-appear as unstaged changes in `git status`. NEVER calls `git reset`, `git checkout`, or any other mutating git command. Use when: the user says "uncommit", "put changes back as unstaged", "undo last jj commit", "move commit into working copy", "unstage from jj", or has a described jj commit they want to re-stage / re-split / amend differently.
jj-workspace
by BlackBeltTechnologyOperating manual for agents working inside a Jujutsu (jj) workspace. Read this when your cwd is under a `.shadow/<name>/` directory or any other `jj workspace add` target. Lists safe vs. forbidden commands in colocated jj+git repos, the basic working-copy mental model, and how to describe and ship work back to trunk via the `jj-workspace-fold-back` skill. Use when: working in any jj workspace, before running `git` commands in a jj-managed cwd, when reviewing or describing changes, when conflicts appear, when asked to commit/push/merge in a jj repo.
pi-dashboard
by BlackBeltTechnologyMonitor and control the pi-dashboard server. List sessions, send prompts, abort runs, spawn new sessions, manage git branches, control flows, and configure the dashboard — all via REST API. Use when you need to interact with other pi sessions, check dashboard health, or orchestrate multi-session workflows.
release-cut
by BlackBeltTechnologyCut a new pi-agent-dashboard release. Promotes `## [Unreleased]` in CHANGELOG.md to a versioned section, bumps all workspace package.json versions per SemVer, commits, tags `v<version>`, and pushes — which triggers the Release workflow that publishes **6 npm packages** (root + shared/extension/server/web/image-fit via `npm publish -ws --include-workspace-root`) and the Electron artifacts and creates a draft GitHub Release. Use when the user says "cut a release", "release vX.Y.Z", "publish a new version", "tag a release".
release-revoke
by BlackBeltTechnologyRevoke or rollback a pi-agent-dashboard release. Deletes the GitHub Release (draft or published), removes the git tag locally and on origin, deprecates the npm package version (since `npm unpublish` is blocked after 72h / for packages with dependents), and optionally reverts the `chore(release): vX.Y.Z` commit. Use when the user says "revoke release", "rollback release", "delete release", "unpublish vX.Y.Z", "yank release".
spec-coherence-check
by BlackBeltTechnologySweep all active OpenSpec proposals for staleness, conflicts, and obsolescence against the current codebase and archived changes. Use when proposals may be outdated, when checking cross-proposal conflicts, or before starting a batch of implementations. Produces a gap-analysis report, updates a priority queue file, and can auto-fix trivial issues or guide conversations for complex ones.
nano-banana-imagegen
by BlackBeltTechnologyGenerate and edit images using Google Gemini image models via the nano-banana CLI. Use when the user asks to create, generate, make, or edit images with AI. Supports text-to-image, image editing, style transfer, and multi-image composition. Trigger on requests like "create an image", "generate a picture", "make me a logo", "edit this photo", "add X to this image".
jj-workspace-fold-back
by BlackBeltTechnologyFold the current jj workspace's commits back onto trunk and push them via `jj git push --bookmark`. NEVER invokes `git commit`, `git merge`, or any other mutating git command. Default flavor preserves the agent's commit history (no squash) and pushes to a feature bookmark. Refuses to run on conflicts, dirty git index, empty working copy, or non-colocated repos. Use when: an agent has finished work in a `.shadow/<name>/` workspace and wants to land the changes on trunk; user says "fold back", "merge workspace", "ship the agent's work", "push the workspace", "land the changes".
dashboard-plugin-scaffold
by BlackBeltTechnologyScaffold a new pi-dashboard plugin in the dashboard monorepo, OR augment an existing pi-extension project on disk with dashboard plugin contributions. Hybrid skill: a single ask_user batch up front, then prescriptive steps the agent follows. Use when the user asks to "create a dashboard plugin", "add dashboard support to my extension", "scaffold a plugin", or similar.
browser
by BlackBeltTechnologyBrowser automation via the `agent-browser` CLI. Use when the user needs to interact with websites or Electron desktop apps — navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, automating browser actions, visual UI verification, responsive checks, hunting console errors, or driving the Pi Dashboard's Electron shell (main window, wizard window, doctor window, tray, native menus). Triggers include "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data", "test this web app", "automate browser", "test responsive", "debug blank page", "automate Slack app", "control VS Code", "attach to Electron app", "screenshot Pi Dashboard", "drive the wizard window".
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
Browse by Category
Explore agent skills organized by their primary use case
Explore the agent skills ecosystem by occupation and creator
SkillMD is not just a keyword search box. It is an open map that organizes public skills by occupation, creator, and repository, helping you see which workflows, judgment criteria, and domain habits people are writing for AI agents.
Then follow creators and GitHub repositories back to the source: compare the skills a team maintains, whether the repo is active, and how the README frames the work before you open, install, or reuse anything.
Use it three ways: learn an unfamiliar field by occupation, study how creators organize skills, then use source context to decide what is worth opening or reusing.
01 Map a field
Browse 23 occupation groups and 867 SOC roles to learn what skills exist in adjacent domains and how they break down real work.
02 Follow creators
Use creator and repository pages to inspect maintained skill collections, recent updates, and source context before trusting a result.
03 Search with sources
Search 1.7M+ collected skills, then use occupation tags, creators, and GitHub source context to decide what is worth opening.
Start with the occupation map, then follow creators and repositories back to real code. SkillMD helps explain why a skill is worth opening, not only what it is named.
Standardizing Agent Capabilities with SKILL.md and Model Context Protocol (MCP)
In the rapidly evolving landscape of artificial intelligence, LLM agents (Large Language Model agents) have transitioned from simple text predictors to autonomous problem solvers. To orchestrate complex, multi-step agentic workflows, developers require a standardized format to specify agent capabilities, prompt instructions, system rules, and database bindings. This is where SKILL.md and the Model Context Protocol (MCP) have emerged as standard developer paradigms. SkillMD serves as the central directory for indexing, exploring, and sharing these critical agent configurations.
Our open-source registry currently tracks over 1.7 million collected SKILL.md configurations and system prompts. By compiling agent configurations from active developers on GitHub, we bridge the gap between prompt engineering research and production execution. Whether you are building agents with Anthropic's Claude Code, OpenAI's GPT-4, Google's Gemini, or local models using Ollama and LlamaIndex, standardized skill definitions ensure your agents behave predictably across different runtime environments.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open-source standard designed to connect LLMs to data sources, developer tools, and external environments. MCP establishes a bidirectional communication channel between client applications (like Cursor, Claude Desktop, or custom agent systems) and servers hosting data or capabilities. Standardizing instructions via SKILL.md enables LLMs to query databases, read local files, execute terminal commands, and integrate third-party APIs. SkillMD allows you to find ready-to-run MCP servers and prompt instructions for various occupations and technical tasks.
The Structure of a Professional SKILL.md File
A valid SKILL.md configuration is designed to be easily read by humans and parsed by LLMs. It contains precise system instructions, trigger conditions, required parameters, and execution examples. Below is the typical architectural blueprint of a professional agent skill:
- Metadata & Core Scope: Declares the name of the skill, author details, target models, and a description of the capability.
- Triggers & Intent Detection: Details semantic triggers that help the agent decide when to invoke this skill.
- System Prompts: Explicit system-level instructions that direct the agent's behavior, personality, safety guardrails, and formatting preferences.
- Capabilities & Tools: Lists the files, databases, or APIs the agent must access to complete the tasks.
- Few-Shot Examples: Demonstrates real inputs and outputs, helping the model generalize behavior through in-context learning.
Optimizing Agent Workflows for Modern LLMs
Writing effective agent skills requires deep knowledge of prompt engineering. With the release of advanced reasoning models like Claude 3.5 Sonnet, ChatGPT o1, and DeepSeek-V3, prompt templates must focus on structured thinking. Developers are encouraged to use XML tags (e.g., <thought>, <context>, and <rules>) to isolate execution boundaries. Standardized prompts prevent agents from suffering from context drift, ensuring that long-running tasks remain aligned with the initial system parameters.
Exploring by SOC Occupations and Creator Profiles
What makes SkillMD unique is its taxonomy. Instead of simple text search, we parse and organize files according to the Standard Occupational Classification (SOC) system. This means you can discover skills written for Computer and Mathematical roles, Business and Financial operations, Legal, Design, and and Educational Instruction fields. By tracking creator profiles, developers can study how different teams organize their custom instructions, compare version updates, and fork public configs for specialized enterprise use cases.
SkillMD operates as a high-performance index running on a fast Go backend and a highly responsive Astro SSR frontend. All search queries execute in milliseconds, featuring smart debouncing to prevent multiple API requests while keeping user data secure. Join our community of developers to standardize your AI agent instructions and optimize your LLM prompting workflows today.
Frequently Asked Questions
A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.